miRNAs play a key role in normal physiology and various diseases such as cancer. However, analyzing miRNA sequencing data is challenging due to the requirement of significant computational resources and bioinformatics expertise. To address this, we present a comprehensive analysis pipeline for deep microRNA sequencing (CAP-miRSeq) that integrates read preprocessing, alignment, mature/precursor/novel miRNA qualification, variant detection in miRNA coding region, and flexible differential expression between experimental conditions. Using well characterized data, we demonstrated the pipeline’s superior performances, flexibilities, and practical use in research and biomarker discovery.
ChIP-RNA-seqPRO is a resource motivated by this current need and provides a strategy that enables the user to profile regulatory associations between epigenomic modifications and co/post-transcriptional processes.
eSNV-Detect v1.0: Reliable Identification of Variants Using RNA-seq Data
A tool used to calculate the estimated sensitivity of fusion finding for an RNA-seq experiment. It plots the estimated sensitivity as a function of the distance to the 3’ end and also calculates the decay rate for the sample.
ICQ-lincRNA (Identification, Characterization, and Quantification of Long Intergenic Non-Coding RNAs), offers an end-to-end solution to identify and annotate expressed lincRNAs in next generation RNA sequencing data. Specifically, ICQ-lincRNA: Conducts ab-initio genome-wide transcript assembly by both Cufflinks and Scripture using Binary Alignment/Map (BAM) files Conducts downstream quantitative analyses including gene count, exon count, overlap with known […]
The MAP-RSeq workflow integrates a suite of open source bioinformatics tools along with in-house developed methods to analyze paired-end RNA-Seq data.
The Ultrafast and Comprehensive lncRNA detection (UClncRNA) pipeline leverages fast transcript assembly and parallel computing tools, multi-step filters for increased specificity to provide comprehensive lncRNA characterization.